All EECS News

Mike Lewicki (Associate Professor of EECS) has received a $1.8M ($815K for CWRU) 4-year NSF grant (together with colleagues at UC Berkeley and UT Austin) for studying motion in natural scenes.

This project seeks to advance our understanding of a fundamental problem in both biological and machine vision: how does a visual system recover 3D scene structure -- such as the layout of the environment, surface shape, or object motion -- from dynamic, 2D images? Computer vision has approached this problem by developing algorithms for recovering specific aspects of a scene, but obtaining general solutions that perform robustly for complex natural scenes and viewing conditions remains a challenge. Biological vision systems have evolved impressive information processing strategies for extracting 3D structure from natural scenes, but the neural representations for doing this are poorly understood and provide little insight into the computational process. This project will pursue an interdisciplinary approach by attempting the understand the universal principles that lie at the heart of this problem in both biological and machine vision systems. Specifically, the project will 1) develop a novel class of computational models that recover and represent 3D scene information by factoring apart the underlying causal structure of images, 2) collect high quality video and range data of dynamic natural scenes under a variety of controlled motion conditions, and 3) test the perceptual implications of these models in psychophysical experiments.

GQ Zhang (Professor of Electrical Engineering and Computer Science and Chief of Medical Informatics at CWRU), Satya Sahoo (Assistant Professor in the division of medical informatics at CWRU), and Amit Sheth (the LexisNexis Ohio Eminent Scholar at Wright State University) delivered a two-hour tutorial titled "The Role of the Semantic Web in Health Informatics" at the ACM SIGHIT International Health Informatics Symposium in Miami, Florida, January 28, 2012. The tutorial was one of only three tutorials selected by the SIGHIT Symposium this year!

Congratulations to Prof. Swarup Bhunia, PhD student Lei Wang and EECS PhD alum Somnath Paul (Currently at Intel Corporation) for receiving the Best Paper Award in the 25th International Conference on VLSI Design for the paper titled "Width-Aware Fine-Grained Dynamic Supply Gating: A Design Methodology for Low-Power Datapath and Memory." The paper presents a novel design solution to greatly reduce the power and heat problem in next-generation processors that go into desktop computers, mobile servers and mobile devices. The work on this paper is sponsored by Intel Corporation. Announcement about the award can be found here: http://vlsiconference.com/vlsi2012/

TyTaylor and Mario Castaneda, 2011 EECS graduates, recently won the Seattle Independent Game Competition with their videogame, “The Bridge.” In August, The Bridge was a finalist in Microsoft’s Dream.Build.Play international videogame competition, where it was won the Honorable Mention for Innovation, and in October, The Bridge was a finalist for the IndieCade international independent game festival in Culver City, CA, where it was a nominee for Best Visuals. The game is also a finalist in the Independent Game Festival (IGF) Student Showcase for the 14'th presentation of its prestigious awards, celebrating the brightest and most innovative creations to come out of universities and games programs from around the world in the past year!

The Bridge is a 2-D logic-based puzzle game that forces the player to reevaluate their preconceptions of physics and perspective. It is Isaac Newton meets M. C. Escher—Manipulate gravity to redefine the ceiling as the floor, and venture through impossible architectures. Explore increasingly difficult worlds, each uniquely detailed and guaranteed to leave the player with a pronounced sense of accomplishment, while immersing the player into a captivating story. The Bridge exemplifies games as an art form, with beautifully hand-drawn art in the style of a black-and-white lithograph.